With the advent of digital photography, consumers are amassing large collections of digital images and videos. The average number of images captures with digital cameras per photographer is still increasing each year. As a consequence, the organization and retrieval of images and videos is already a problem for the typical consumer. Currently, the length of time spanned by a typical consumer's digital image collection is only a few years. The organization and retrieval problem will continue to grow as the length of time spanned by the average digital image and video collection increases.
One of the most fundamental subjects of consumer photography is people. Furthermore, in a given collection of digital images and videos, certain people tend to occur frequently. For example, it is common for most images captured by new parents to contain their new baby. Consumers desire the ability to find all images from their collection containing a specific person. However, this is technically a very difficult task. For example, the baby will grow from baby to toddler to child to adult and radically change in appearance.
There exists many image processing packages that attempt to recognize people for security or other purposes. Some examples are the FaceVACS face recognition software from Cognitec Systems GmbH and the Facial Recognition SDKs from Imagis Technologies Inc. and Identix Inc. These packages are primarily intended for security-type applications where the person faces the camera under uniform illumination, frontal pose and neutral expression. These methods are not suited for use in personal consumer images due to the large variations in pose, illumination, expression and face size encountered in images in this domain. Furthermore, these systems are targeted for use on adult faces and cannot successfully recognize an image of a particular person of interest at any age.
Several image processing techniques have been described for detecting the age of a person from a digital image. For example, Lobo and Kwon describe a method of classifying the age of human faces in digital images in U.S. Pat. No. 5,781,650. They perform facial measurements and a wrinkle analysis using snakes and classify the age of the person into the categories of: baby (up to about 3 years), junior (3 to 40 years), and senior (over 40 years). This method does not discuss the problem of recognizing the identity of people in the image. Other image processing techniques are known which us facial recognition. For example, U.S. Published Patent Application US 2004/0247177A1 uses eigenfaces to characterize the pixel density pattern of a subject's face. All of the above techniques suffer from problems and can misidentify persons of interest.